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Background and objective Although mental health is always a major concern, particularly for airline pilots, knowledge of and attitudes toward mental health have not always been emphasized for safe operations in the aviation industry. Fear of self-reporting, stigmas, and lack of knowledge about mental health conditions are prevalent in this industry. The purpose of our research was to examine pilots' perceptions of mental health issues, the resources available to them, and the reasons they may or may not report these issues. Methods We conducted a qualitative, phenomenological study in which 21 commercial pilots were interviewed to better understand their perceptions of mental health issues, available self-help resources, and rationale for failing to report mental health issues. Results The results of our analysis using NVivo software showed that pilots neither reported the issues nor trusted the processes meant to address mental health issues. Three themes emerged from the research: (1) pilots avoid discussing mental health issues for fear of repercussions, (2) although resources exist, pilots generally distrust the confidentiality of reporting systems, and (3) pilots honestly believe that reporting any mental health issue will be devastating to their careers. Conclusions Airline companies and the Federal Aviation Administration (FAA) need to change processes and instill a sense of trust in reporting systems among pilots so that they feel safe reporting mental health concerns and receive improved treatment. This can lead to more accurate reporting of conditions and ensure safe flight operations.
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Objective: To investigate collegiate aviation pilots' quality of sleep and psychological distress levels. Participants: Collegiate aviation pilots from a Code of Federal Regulations Part 141 four-year degree-awarding university in central Florida (N = 192). Method: The Pittsburgh Sleepiness Quality Index and the Kessler Psychological Distress Scale were utilized to assess the participants' subjective quality sleep and psychological distress levels, respectively. A Spearman's rank-order correlation was run to assess the relationship between quality sleep and distress levels in collegiate aviation student pilots. Results: The prevalence of poor sleep quality among the collegiate aviation pilots was 69%. Mild or severe psychological distress was experienced by 32% (n = 61) of the pilots. There was a strong, positive association between quality sleep and psychological distress (rs (192) = .716, p < .05). Conclusion: Results suggested collegiate aviation programs should promote explicit strategies for students to improve their sleep habits and well-being.
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INTRODUCTION: Complex risk scores have limited applicability in the assessment of patients with myocardial infarction (MI). In this work, the authors aimed to develop a simple to use clinical score to stratify the in-hospital mortality risk of patients with MI at first medical contact. METHODS: In this single-center prospective registry assessing 1504 consecutively admitted patients with MI, the strongest predictors of in-hospital mortality were selected through multivariate logistic regression. The KAsH score was developed according to the following formula: KAsH=(Killip class×Age×Heart rate)/systolic blood pressure. Its predictive power was compared to previously validated scores using the DeLong test. The score was categorized and further compared to the Killip classification. RESULTS: The KAsH score displayed excellent predictive power for in-hospital mortality, superior to other well-validated risk scores (AUC: KAsH 0.861 vs. GRACE 0.773, p<0.001) and robust in subgroup analysis. KAsH maintained its predictive capacity after adjustment for multiple confounding factors such as diabetes, heart failure, mechanical complications and bleeding (OR 1.004, 95% CI 1.001-1.008, p=0.012) and reclassified 81.5% of patients into a better risk category compared to the Killip classification. KAsH's categorization displayed excellent mortality discrimination (KAsH 1: 1.0%, KAsH 2: 8.1%, KAsH 3: 20.4%, KAsH 4: 55.2%) and better mortality prediction than the Killip classification (AUC: KAsH 0.839 vs. Killip 0.775, p<0.0001). CONCLUSION: KAsH, an easy to use score calculated at first medical contact with patients with MI, displays better predictive power for in-hospital mortality than existing scores.